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Linguistics-based formalization of the antibody language as a basis for antibody language models., , , , , , and . Nat. Comput. Sci., 4 (6): 412-422 (June 2024)Advancing protein language models with linguistics: a roadmap for improved interpretability., , , , , , and . CoRR, (2022)Hopfield Networks is All You Need, , , , , , , , , and 6 other author(s). (2020)cite arxiv:2008.02217Comment: 10 pages (+ appendix); 12 figures; Blog: https://ml-jku.github.io/hopfield-layers/; GitHub: https://github.com/ml-jku/hopfield-layers.ImmunoLingo: Linguistics-based formalization of the antibody language., , , , , , and . CoRR, (2022)Improving generalization of machine learning-identified biomarkers using causal modelling with examples from immune receptor diagnostics., , , , , , , and . Nat. Mac. Intell., 6 (1): 15-24 (2024)CompAIRR: ultra-fast comparison of adaptive immune receptor repertoires by exact and approximate sequence matching., , , and . Bioinform., 38 (17): 4230-4232 (2022)Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery., , , , , , , , , and 3 other author(s). Briefings Bioinform., (2022)Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction., , , , , , , , , and 15 other author(s). Nat. Comput. Sci., 2 (12): 845-865 (2022)Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences., , , , , , , , , and 6 other author(s). Bioinform., 36 (6): 1731-1739 (2020)Access to ground truth at unconstrained size makes simulated data as indispensable as experimental data for bioinformatics methods development and benchmarking., and . Bioinform., 38 (21): 4994-4996 (October 2022)